Not applicable.
Historically, the term xe2x80x9cquantitative traitxe2x80x9d has been used to describe variability in expression of a phenotypic trait that shows continuous variability and is the net result of multiple genetic loci possibly interacting with each other and/or with the environment. To describe a broader phenomenon, the term xe2x80x9ccomplex traitxe2x80x9d has been used to describe any trait that does not exhibit classic Mendelian inheritance attributable to a single genetic locus (Lander and Schork, Science 265:2037 (1994)). The distinction between the terms, for purposes of this disclosure, is subtle and therefore the two terms will be used synonymously.
It is estimated that 98% of the economically important phenotypic traits in domesticated plants are quantitative traits. These traits are classified as oligogenic or polygenic based on the perceived numbers and magnitudes of segregating genetic factors affecting the variability in expression of the phenotypic trait.
The development of ubiquitous polymorphic genetic markers that span the genome (e.g., RFLP) has made it possible for quantitative and molecular geneticists to investigate what Edwards, et al., in Genetics 115:113 (1987) referred to as quantitative trait loci (QTL), as well as their numbers, magnitudes and distributions. QTL include genes that control, to some degree, numerically representable phenotypic traits that are usually continuously distributed within a family of individuals as well as within a population of families of individuals. An experimental paradigm has been developed to identify and analyze QTL. This paradigm involves crossing two inbred lines, genotyping multiple marker loci and evaluating one to several quantitative phenotypic traits among the segregating progeny derived from the cross. The QTL are then identified on the basis of significant statistical associations between the genotypic values and the phenotypic variability among the segregating progeny. This experimental paradigm is ideal in that the parental lines of the F1 generation have the same degree of linkage, all of the associations between the genotype and phenotype in the progeny are informative and linkage disequilibrium between the genetic loci and phenotypic traits is maximized.
Because relatively few numbers of progeny are studied, the experiments described above lack the necessary statistical power to identify QTL for most traits of economic importance in breeding populations, for example, maize, sorghum, soybean, canola, etc. Additionally, the lack of statistical power produces biased estimates of the QTL that are identified. Additional imprecision is introduced in extrapolating the identification of QTL to the progeny of genetically different parents within a breeding population.
General forms of genetic and statistical models for predicting breeding values are known in the art (Henderson, Biometrics 31:423 (1975)). Specific models have also been proposed for QTL identification in animal breeding (Soller and Genizi, Biometrics 34:47 (1978); and Fernando and Grossman, Genet. Sel. Evol. 21:467 (1989)) and human populations (Goldgar, Am. J. Hum. Genet. 47:957 (1990)). However, statistical models have not been developed for plant breeding populations. Thus, there remains a need in the art for methods that take account of and are applicable to determining QTL in commercially important plant breeding populations. The invention herein satisfies this need.
This invention provides methods of identifying quantitative trait loci in a mixed defined plant population comprising multiple plant families. The method operates by quantifying a phenotypic trait across lines sampled from the population, identifying at least one genetic marker associated with the phenotypic trait by screening a set of markers and identifying the quantitative trait loci based on the association of the phenotypic trait and the genetic marker(s).
In one embodiment, the plant population consists of diploid plants, either hybrid or inbred, preferably maize, soybean, sorghum, wheat, sunflower, and canola. In a most preferred embodiment, the plant population consists of Zea mays. 
The phenotypic traits associated with the QTL are quantitative, meaning that, in some context, a numerical value can be ascribed to the trait. Preferred phenotypic traits include, but are not limited to, grain yield, grain moisture, grain oil, root lodging, stalk lodging, plant height, ear height, disease resistance, and insect resistance.
In a preferred embodiment, the genetic markers associated with the QTL are restriction fragment length polymorphisms (RFLP), isozyme markers, allele specific hybridization (ASH), amplified variable sequences of the plant genome, self-sustained sequence replication, simple sequence repeats (SSR), and arbitrary fragment length polymorphisms (AFLP). In another preferred embodiment, at least two genetic markers are associated with the QTL and are identified by high throughput screening.
The association of the genetic loci and the phenotypic trait is determined through specified statistical models. In a preferred embodiment, the statistical models are linear models with fixed effects and random effects. In a particularly preferred embodiment, the statistical model is a mixed effects model wherein the phenotypic trait of the progeny of one line from one family in the breeding population is evaluated in topcross combination with a tester parent.
In yet another embodiment, the identification of QTL allows for the marker assisted selection of a desired phenotypic trait in the progeny of a diploid plant breeding population selected from the group consisting of maize, soybean, sorghum, wheat, sunflower, and canola. In a particularly preferred embodiment, the plant population consists of Zea mays. In yet another embodiment, the phenotypic trait selected for includes, but is not limited to, yield, grain moisture, grain oil, root lodging, stalk lodging, plant height, ear height, disease resistance, and insect resistance.
In another aspect of the invention, plants selected by the methods described above are provided. In addition to plants created by selfing and sexual crosses, cloned plants are described, as are transgenic plants. The transgenic plants contain nucleic acid sequences associated with a desired QTL.